{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Thermal Conductivity from EMD\n",
    "# 1. Introduction\n",
    "- In this example, we use the EMD (Green-Kubo) method to calculate the lattice thermal conductivity of graphene at 300 K and zero pressure."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Relevant Functions\n",
    "- The inputs/outputs for GPUMD are processed using the [Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/) and the [thermo](https://github.com/AlexGabourie/thermo) package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import *\n",
    "from ase.build import graphene_nanoribbon\n",
    "from thermo.gpumd.data import load_hac\n",
    "from thermo.gpumd.io import ase_atoms_to_gpumd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Preparing the Inputs\n",
    "- The [xyz.in](https://gpumd.zheyongfan.org/index.php/The_xyz.in_input_file)  file used is the same as in density of states tutorial.\n",
    "- We use a Tersoff potential [[Tersoff 1989]](https://doi.org/10.1103/PhysRevB.39.5566) parameterized by Lindsay *et al.* [[Lindsay 2010]](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.81.205441).\n",
    "- Note that the thickness of the graphene sheet is set to 3.35 $\\mathring A$ according to the convention in the literature. This thickness is needed to calculate an effective 3D thermal conductivity for a 2D material.\n",
    "\n",
    "## Generate the  [xyz.in](https://gpumd.zheyongfan.org/index.php/The_xyz.in_input_file) file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Atoms(symbols='C8640', pbc=[True, True, False], cell=[149.64918977395098, 155.52, 3.35])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gnr = graphene_nanoribbon(60, 36, type='armchair', sheet=True, vacuum=3.35/2, C_C=1.44)\n",
    "gnr.euler_rotate(theta=90)\n",
    "l = gnr.cell.lengths()\n",
    "gnr.cell = gnr.cell.new((l[0], l[2], l[1]))\n",
    "l = l[2]\n",
    "gnr.center()\n",
    "gnr.pbc = [True, True, False]\n",
    "gnr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ase_atoms_to_gpumd(gnr, M=3, cutoff=2.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The first few lines of the [xyz.in](https://gpumd.zheyongfan.org/index.php/The_xyz.in_input_file) file are:\n",
    "```\n",
    "8640 3 2.1 0 0 0\n",
    "1 1 0 149.649 155.52 3.35\n",
    "0 1.24708 0 0 12\n",
    "0 0 0.72 0 12\n",
    "0 0 2.16 0 12\n",
    "0 1.24708 2.88 0 12\n",
    "```\n",
    "\n",
    "- Explanations for the first line:\n",
    "  - The first number states that the number of particles is 8640.\n",
    "  - The second number in this line, 3, is good for graphene described by the Tersoff potential because no atom can have more than 3 neighbor atoms at room temperature. Making this number larger only results in more memory usage. If this number is not large enough, GPUMD will give an error message and exit.\n",
    "  - The next number, 2.1, means that the initial cutoff distance for the neighbor list construction is 2.1 A. Here, we only need to consider the first nearest neighbors. Any number larger than the first nearest neighbor distance and smaller than the second nearest neighbor distance is OK here. Note that we will also not update the neighbor list. There is no such need in this problem. \n",
    "  - The remaining three zeros in the first line mean:\n",
    "    - the box is orthogonal;\n",
    "    - the initial velocities are not contained in this file;\n",
    "    - there are no grouping methods defined here.\n",
    "\n",
    "\n",
    " - Explanations for the second line:\n",
    "   - The numbers 1 1 0 mean that the x and y (in-plane) directions are periodic and the z direction is open (free).\n",
    "   - The remaining three numbers are the box lengths in the three directions. The box length in a free direction is chosen based on some convention. This number will only affect the system volume.\n",
    "\n",
    "- Starting from the third line, the numbers in the first column are all 0 here, which means that all the atoms are of type 0 (single atom-type system). The next three columns are the initial coordinates of the atoms. The last column gives the masses of the atoms. Here, we consider isotopically pure C-12 crystal, but this Jupyter notebook will generate an [xyz.in](https://gpumd.zheyongfan.org/index.php/The_xyz.in_input_file) file using the average of the various isotopes of C. In some applications, one can consider mass disorder in a flexible way."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The <code>run.in</code> file:\n",
    "The <code>run.in</code> input file is given below:<br>\n",
    "```\n",
    "potential    potentials/tersoff/Graphene_Lindsay_2010_modified.txt\n",
    "velocity     300\n",
    "\n",
    "# equilibration\n",
    "ensemble     npt_ber 300 300 0.01 0 0 0 0.0005\n",
    "time_step    1\n",
    "dump_thermo  1000\n",
    "run          1000000\n",
    "    \n",
    "# production\n",
    "ensemble     nve\n",
    "compute_hac  20 50000 10\n",
    "run          10000000\n",
    "```\n",
    "- The first line uses the [potential](https://gpumd.zheyongfan.org/index.php/The_potential_keyword) keyword to define the potential to be used, which is specified in the file [Graphene_Lindsay_2010_modified.txt](https://github.com/brucefan1983/GPUMD/blob/master/potentials/tersoff/Graphene_Lindsay_2010_modified.txt).\n",
    "\n",
    "- The second line uses the [velocity](https://gpumd.zheyongfan.org/index.php/The_velocity_keyword) keyword and sets the velocities to be initialized with a temperature of 300 K. \n",
    "\n",
    "- There are two runs.\n",
    "  - The first [run](https://gpumd.zheyongfan.org/index.php/The_run_keyword) serves as the equilibration stage, where the NPT [ensemble](https://gpumd.zheyongfan.org/index.php/The_ensemble_keyword) (the Berendsen barostat) is used. The temperature is 300 K and the pressures are zero in all the directions. The coupling constants are 0.01 (dimensionless) and 0.0005 (in the natural unit system adopted by GPUMD) for the thermostat and the barostat, respectively. The [time_step](https://gpumd.zheyongfan.org/index.php/The_time_step_keyword) for integration is 1 fs. There are $10^6$ steps (1 ns) for this [run](https://gpumd.zheyongfan.org/index.php/The_run_keyword) and the thermodynamic quantities will be output every 1000 steps.\n",
    "  - The second [run](https://gpumd.zheyongfan.org/index.php/The_run_keyword) is for production. Here, the NVE [ensemble](https://gpumd.zheyongfan.org/index.php/The_ensemble_keyword) is used. The line with the [compute_hac](https://gpumd.zheyongfan.org/index.php/The_compute_hac_keyword) keyword means that heat currents will be recorded every 20 steps (20 fs), 50000 HAC data (the maximum correlation time is then about 1 ns) will be calculated, and the HAC are averaged for every 10 data points before written out. The production time is 10 ns ($10^7$ steps), which is 10 times as long as the maximum correlation time. This is a reasonable choice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Results and Discussion\n",
    "### Computation Time\n",
    "- The results below are from three independent runs, which took about two hours in total using a Tesla K40 card."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure Properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "aw = 2\n",
    "fs = 16\n",
    "font = {'size'   : fs}\n",
    "matplotlib.rc('font', **font)\n",
    "matplotlib.rc('axes' , linewidth=aw)\n",
    "\n",
    "def set_fig_properties(ax_list):\n",
    "    tl = 8\n",
    "    tw = 2\n",
    "    tlm = 4\n",
    "    \n",
    "    for ax in ax_list:\n",
    "        ax.tick_params(which='major', length=tl, width=tw)\n",
    "        ax.tick_params(which='minor', length=tlm, width=tw)\n",
    "        ax.tick_params(which='both', axis='both', direction='in', right=True, top=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot HAC (heat current autocorrelations) & RTC (running thermal conductivity)\n",
    " - The [hac.out](https://gpumd.zheyongfan.org/index.php/The_hac.out_output_file) output file is loaded and processed to create the following figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['run0', 'run1', 'run2'])\n",
      "dict_keys(['t', 'jxijx', 'jxojx', 'jyijy', 'jyojy', 'jzjz', 'kxi', 'kxo', 'kyi', 'kyo', 'kz'])\n"
     ]
    }
   ],
   "source": [
    "hac = load_hac([50000]*3, [10]*3)\n",
    "print(hac.keys())\n",
    "print(hac['run0'].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = hac['run0']['t']\n",
    "hac_ave_i = np.zeros(hac['run0']['jxijx'].shape[0])\n",
    "hac_ave_o = np.zeros_like(hac_ave_i)\n",
    "ki_ave, ko_ave = np.zeros_like(hac_ave_i), np.zeros_like(hac_ave_o)\n",
    "for runkey in hac.keys():\n",
    "    hac_ave_i += hac[runkey]['jxijx']+hac[runkey]['jyijy']\n",
    "    hac_ave_o += hac[runkey]['jxojx']+hac[runkey]['jyojy']\n",
    "    ki_ave += (hac[runkey]['kxi']+hac[runkey]['kyi'])\n",
    "    ko_ave += (hac[runkey]['kxo']+hac[runkey]['kyo'])\n",
    "hac_ave_i /= hac_ave_i.max()\n",
    "hac_ave_o /= hac_ave_o.max()\n",
    "ki_ave /= 6.\n",
    "ko_ave /= 6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(figsize=(12,10))\n",
    "subplot(2,2,1)\n",
    "set_fig_properties([gca()])\n",
    "loglog(t, hac_ave_i, color='C3')\n",
    "loglog(t, hac_ave_o, color='C0')\n",
    "xlim([1e-1, 1e3])\n",
    "ylim([1e-4, 1])\n",
    "xlabel('Correlation Time (ps)')\n",
    "ylabel('Normalized HAC')\n",
    "title('(a)')\n",
    "\n",
    "subplot(2,2,2)\n",
    "set_fig_properties([gca()])\n",
    "for runkey in hac.keys():\n",
    "    plot(hac[runkey]['t'], (hac[runkey]['kxi']+hac[runkey]['kyi'])/2, color='C7',alpha=0.5)\n",
    "plot(t, ki_ave, color='C3', linewidth=3)\n",
    "xlim([0, 1000])\n",
    "gca().set_xticks(range(0,1001,200))\n",
    "ylim([0, 1500])\n",
    "gca().set_yticks(range(0,1501,500))\n",
    "xlabel('Correlation Time (ps)')\n",
    "ylabel(r'$\\kappa^{in}$ (W/m/K)')\n",
    "title('(b)')\n",
    "\n",
    "subplot(2,2,3)\n",
    "set_fig_properties([gca()])\n",
    "for runkey in hac.keys():\n",
    "    plot(hac[runkey]['t'], (hac[runkey]['kxo']+hac[runkey]['kyo'])/2, color='C7',alpha=0.5)\n",
    "plot(t, ko_ave, color='C0', linewidth=3)\n",
    "xlim([0, 1000])\n",
    "gca().set_xticks(range(0,1001,200))\n",
    "ylim([0, 1500])\n",
    "gca().set_yticks(range(0,4001,1000))\n",
    "xlabel('Correlation Time (ps)')\n",
    "ylabel(r'$\\kappa^{out}$ (W/m/K)')\n",
    "title('(c)')\n",
    "\n",
    "subplot(2,2,4)\n",
    "set_fig_properties([gca()])\n",
    "plot(t, ko_ave, color='C0', linewidth=3)\n",
    "plot(t, ki_ave, color='C3', linewidth=3)\n",
    "plot(t, ki_ave + ko_ave, color='k', linewidth=3)\n",
    "xlim([0, 1000])\n",
    "gca().set_xticks(range(0,1001,200))\n",
    "ylim([0, 1500])\n",
    "gca().set_yticks(range(0,4001,1000))\n",
    "xlabel('Correlation Time (ps)')\n",
    "ylabel(r'$\\kappa$ (W/m/K)')\n",
    "title('(d)')\n",
    "\n",
    "tight_layout()\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thermal conductivity results for pristine graphene at 300 K from EMD simulations. **(a)** Normalized HAC as a function of correlation time for the in-plane and out-of-plane components. **(b)** Individual (thin lines) and averaged (thick line) RTC as a function of correlation time for the in-plane component. **(c)** Individual (thin lines) and averaged (thick line) RTC as a function of correlation time for the out-of-plane component. **(d)** Averaged RTC as a function of correlation time for various components."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results\n",
    "- As the system is essentially isotropic in the planar directions, we only consider a scalar thermal conductivity $\\kappa=(\\kappa_{xx}+\\kappa_{yy})/2$ for the 2D system. However, we consider the *in-out decomposition* as introduced in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309).\n",
    "- From **(a)**, we can see that the in-plane component and the out-of-plane component of the HAC have different time scales. The latter decays much more slowly. \n",
    "- Panel **(b)** shows the individual and averaged RTCs for the in-plane component $\\kappa^{\\rm in}(t)$. The averaged RTC converges to about 1000 W/m/K at around 100 ps. \n",
    "- Panel **(c)** shows the individual and averaged RTCs for the out-of-plane component $\\kappa^{\\rm out}(t)$, and the convergence property is not very clear here. This is because the out-of-plane component converges very slowly and three independent simulations (each with 10 ns) are not enough to give accurate results. \n",
    "- Summing up $\\kappa^{\\rm in}(t)$ and $\\kappa^{\\rm out}(t)$, we get $\\kappa^{\\rm tot}(t)$, as shown in panel **(d)**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion\n",
    "- Accurately calculating thermal conductivity of graphene using the EMD method can be a very time consuming task. The results we presented here are from three independent simulations with a total production time of 30 ns. It can been seen that the HAC data already become very noisy when the correlation time is 100 ps. To obtain accurate results, one needs to do many independent simulations. Much more accurate data were presented in Fig. 2 of [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309). Here are the simulation parameters used in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) which differ from those used in this example:\n",
    "  - The simulation cell size used in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) is larger, which is about 25 nm x 25 nm (24000 atoms), instead of 15 nm x 15 nm (8640 atoms) here.\n",
    "  - The maximum correlation time used in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) is larger, which is 10 ns, instead of 1 ns here.\n",
    "  - The production time used in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) for one independent simulation is larger, which is 50 ns, instead of 10 ns here.\n",
    "  - There were 100 independent simulations in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309), instead of 3 here. Therefore, the total production time used in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) is 5000 ns.\n",
    "  - Each independent simulation in [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309) took about 10 GPU hours (using Tesla K40) and about 1000 GPU hours were used to obtain the results shown in Fig. 2 of [[Fan 2017]](https://doi.org/10.1103/PhysRevB.95.144309).\n",
    "  - We see that the EMD method can be very time consuming. A more efficient method of computing thermal conductivity is the HNEMD method, which is discussed in HNEMD tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. References\n",
    "- [Fan 2017] Zheyong Fan, Luiz Felipe C. Pereira, Petri Hirvonen, Mikko M. Ervasti, Ken R. Elder, Davide Donadio, Tapio Ala-Nissila, and Ari Harju, [Thermal conductivity decomposition in two-dimensional materials: Application to graphene](https://doi.org/10.1103/PhysRevB.95.144309), Phys. Rev. B **95**, 144309 (2017).\n",
    "- [Lindsay 2010] L. Lindsay and D.A. Broido, [Optimized Tersoff and Brenner emperical potential parameters for lattice dynamics and phonon thermal transport in carbon nanotubes and graphene](https://doi.org/10.1103/PhysRevB.39.5566), Phys. Rev. B, **81**, 205441 (2010).\n",
    "- [Tersoff 1989] J. Tersoff, [Modeling solid-state chemistry: Interatomic potentials for multicomponent systems](https://doi.org/10.1103/PhysRevB.39.5566), Phys. Rev. B 39, 5566(R) (1989)."
   ]
  }
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